Skip to main content

Deception of the “Elephant in the Room”: Invisible Auditing Multi-party Conversations to Support Caregivers in Cognitive Behavioral Group Therapies

  • 1445 Accesses

Part of the Lecture Notes in Computer Science book series (LNISA,volume 12183)

Abstract

One of the biggest challenges in Group Therapy is to track each patient’s experience and feeling without him/her noticing. Altering the familiarity of the mutual support group routine may weaken the therapeutic efficacy of the intervention. It must be avoided the “Elephant in the room’s Effect”: everyone knows is being observed and acts consequently. Therapists struggle and spend years of training on developing the skills they need to “silently” monitor all patients at the same time. From our perspective, we wonder whether and how technology can be a support for therapists in such a challenging task. More precisely, how to provide them with a non-invasive support tool that is invisible to the end-users, but at the same time ever-present for the caregivers. Basically, we asked ourselves: Can we deceive “the Elephant in the room”? Therapists may benefit from automatic measures indicating how the participants perceive the session and gathering the participants’ feedback is one path to develop valuable mutual support interventions. Our work describes the design, development and assessment of a non-invasive tool to monitor a Group Session.

Keywords

  • Psychology and cognition: psychological application for user interface
  • Technology: tools for HCI
  • UX and usability: evaluation/comparison of usability and UX methods
  • UX and usability: user experience

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-030-49065-2_1
  • Chapter length: 20 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   84.99
Price excludes VAT (USA)
  • ISBN: 978-3-030-49065-2
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   109.99
Price excludes VAT (USA)
Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.

References

  1. Pfeiffer, P.N., Heisler, M., Piette, J.D., Rogers, M.A.M., Valenstein, M.: Efficacy of peer support interventions for depression: a meta-analysis. Gen. Hosp. Psychiatry 33(1), 29–36 (2011)

    CrossRef  Google Scholar 

  2. Stead, L.F., Carroll, A.J., Lancaster, T.: Group behaviour therapy programmes for smoking cessation. Cochrane Database Syst. Rev. (3) (2017). Article no. CD001007. https://doi.org/10.1002/14651858.CD001007.pub3

  3. Cameron, L.D., Booth, R.J., Schlatter, M., Ziginskas, D., Harman, J.E.: Changes in emotion regulation and psychological adjustment following use of a group psychosocial support program for women recently diagnosed with breast cancer. Psycho-Oncol.: J. Psychol. Soc. Behav. Dimensions Cancer 16(3), 171–180 (2007)

    Google Scholar 

  4. Breitbart, W., Rosenfeld, B., Pessin, H., Applebaum, A., Kulikowski, J., Lichtenthal, W.G.: Meaning-centered group psychotherapy: an effective intervention for improving psychological well-being in patients with advanced cancer. J. Clin. Oncol. 33(7), 749 (2015)

    CrossRef  Google Scholar 

  5. Seebohm, P., Chaudhary, S., Boyce, M., Elkan, R., Avis, M., Munn-Giddings, C.: The contribution of self-help/mutual aid groups to mental well-being. Health Soc. Care Community 21(4), 391–401 (2013)

    CrossRef  Google Scholar 

  6. Ruini, C., Belaise, C., Brombin, C., Caffo, E., Fava, G.A.: Well-being therapy in school settings: a pilot study. Psychother. Psychosom. 75(6), 331–336 (2006)

    CrossRef  Google Scholar 

  7. Friedman, E.M., Ruini, C., Foy, R., Jaros, L., Sampson, H., Ryff, C.D.: Lighten UP! A community-based group intervention to promote psychological well-being in older adults. Aging Ment. Health 21(2), 199–205 (2017)

    CrossRef  Google Scholar 

  8. Hawton, K.E., Salkovskis, P.M., Kirk, J.E., Clark, D.M.: Cognitive Behaviour Therapy for Psychiatric Problems: A Practical Guide. Oxford University Press, Oxford (1989)

    Google Scholar 

  9. Stott, J., Charlesworth, G., Scior, K.: Measures of readiness for cognitive behavioural therapy in people with intellectual disability: a systematic review. Res. Dev. Disabil. 60(2017), 37–51 (2017)

    CrossRef  Google Scholar 

  10. McConachie, H., et al.: Group therapy for anxiety in children with autism spectrum disorder. Autism 18(6), 723–732 (2014)

    CrossRef  Google Scholar 

  11. Willets, L., Mooney, P., Blagden, N.: Social climate in learning disability services. J. Intellect. Disabil. Offending Behav. 5(1), 24–37 (2014)

    CrossRef  Google Scholar 

  12. Webster, J.J., Kit, C.: Tokenization as the initial phase in NLP. In: COLING 1992: The 15th International Conference on Computational Linguistics, vol. 4 (1992)

    Google Scholar 

  13. Plisson, J., Lavrac, N., Mladenic, D., et al.: A rule based approach to word lemmatization. In: Proceedings of IS-2004, pp. 83–86 (2004)

    Google Scholar 

  14. Màrquez, L., Rodríguez, H.: Part-of-speech tagging using decision trees. In: Nédellec, C., Rouveirol, C. (eds.) ECML 1998. LNCS, vol. 1398, pp. 25–36. Springer, Heidelberg (1998). https://doi.org/10.1007/BFb0026668

    CrossRef  Google Scholar 

  15. Straková, J., Straka, M., Hajič, J.: Open-source tools for morphology, lemmatization, POS tagging and named entity recognition. In: Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pp. 13–18 (2014)

    Google Scholar 

  16. Loper, E., Bird, S.: NLTK: the natural language toolkit. arXiv preprint arXiv:cs/0205028 (2002)

  17. Pinto, A., Gonçalo Oliveira, H., Oliveira Alves, A.: Comparing the performance of different NLP toolkits in formal and social media text. In: 5th Symposium on Languages, Applications and Technologies (SLATE 2016). Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik (2016)

    Google Scholar 

  18. Apple: Apple Natural Language (2019). https://developer.apple.com/documentation/naturallanguage. Accessed Sept 2019

  19. IBM 2019: IBM Natural Language Understanding (2019). https://www.ibm.com/watson/services/natural-language-understanding/. Accessed Sept 2019

  20. Amazon: Amazon Comprehend (2019). https://aws.amazon.com/comprehend/. Accessed Sept 2019

  21. Google: Google Natural Language (2019). https://cloud.google.com/natural-language/?hl=en. Accessed Sept 2019

  22. Liu, F., Liu, F., Liu, Y.: A supervised framework for keyword extraction from meeting transcripts. IEEE Trans. Audio Speech Lang. Process. 19(3), 538–548 (2010)

    CrossRef  Google Scholar 

  23. Galley, M.: Automatic summarization of conversational multi-party speech (2006)

    Google Scholar 

  24. Ziegler, J., Jerroudi, Z.E., Böhm, K.: Generating semantic contexts from spoken conversation in meetings. In: Proceedings of the 10th International Conference on Intelligent User Interfaces, pp. 290–292. ACM (2005)

    Google Scholar 

  25. El-Assady, M., Sevastjanova, R., Gipp, B., Keim, D., Collins, C.: NEREx: named-entity relationship exploration in multi-party conversations. In: Computer Graphics Forum, vol. 36, pp. 213–225. Wiley Online Library (2017)

    Google Scholar 

  26. Li, J., Liao, M., Gao, W., He, Y., Wong, K.-F.: Topic extraction from microblog posts using conversation structures. In: ACL (1). World Scientific (2016)

    Google Scholar 

  27. de Bayser, M.G., Guerra, M.A., Cavalin, P.R., Pinhanez, C.S.: Specifying and implementing multi-party conversation rules with finite-state-automata. In: AAAI Workshops (2018)

    Google Scholar 

  28. Vázquez, M., Carter, E.J., McDorman, B., Forlizzi, J., Steinfeld, A., Hudson, S.E.: Towards robot autonomy in group conversations: understanding the effects of body orientation and gaze. In: 2017 12th ACM/IEEE International Conference on Human-Robot Interaction (HRI), pp. 42–52 (2017)

    Google Scholar 

  29. Sapru, A., Bourlard, H.: Detecting speaker roles and topic changes in multiparty conversations using latent topic models. In: Fifteenth Annual Conference of the International Speech Communication Association (2014)

    Google Scholar 

  30. Lucas-Carrasco, R., Salvador-Carulla, L.: Life satisfaction in persons with intellectual disabilities. Res. Dev. Disabil. 33(4), 1103–1109 (2012)

    CrossRef  Google Scholar 

  31. Evans, C., et al.: Towards a standardised brief outcome measure: psychometric properties and utility of the CORE-OM. Br. J. Psychiatry 180(1), 51–60 (2002)

    CrossRef  Google Scholar 

  32. Margison, F., et al.: CORE: clinical outcomes in routine evaluation. J. Ment. Health 9(3), 247–255 (2000)

    CrossRef  Google Scholar 

  33. Majani, G., et al.: A new instrument in quality-of-life assessment: the satisfaction profile (SAT-P). Int. J. Ment. Health 28(3), 77–82 (1999)

    CrossRef  Google Scholar 

  34. Chin, J.P., Diehl, V.A., Norman, K.L.: Development of an instrument measuring user satisfaction of the human-computer interface. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 213–218. ACM (1988)

    Google Scholar 

  35. Diener, E.: Assessing subjective well-being: progress and opportunities. Soc. Indic. Res. 31(2), 103–157 (1994)

    CrossRef  Google Scholar 

  36. Tobia, V., Greco, A., Steca, P., Marzocchi, G.M.: Children’s wellbeing at school: a multi-dimensional and multi-informant approach. J. Happiness Stud. 20(3), 841–861 (2019)

    CrossRef  Google Scholar 

  37. Shneiderman, B., Norman, K.: Questionnaire for User Interface Satisfaction (QUIS), Designing the User Interface: Strategies for Effective Human-Computer Interaction. Addison-Wesley Publ. Co., Reading (1992)

    Google Scholar 

Download references

Acknowledgements

This research was supported by “Psychotherapy School AREA G” and “Fraternità e Amicizia No-profit”. We thank our consultant, Mrs. Barbara Moro from AREA G. who provided insight and expertise that greatly assisted the research. We would also like to show our gratitude to Miss Fiorella Gillino, Mr Antonio Montinaro, Miss Federica Corbella and Miss Emily Luciani and all AREA G. therapists and students for sharing their pearls of wisdom with us during the course of this research.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Marco Mores .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Beccaluva, E. et al. (2020). Deception of the “Elephant in the Room”: Invisible Auditing Multi-party Conversations to Support Caregivers in Cognitive Behavioral Group Therapies. In: Kurosu, M. (eds) Human-Computer Interaction. Human Values and Quality of Life. HCII 2020. Lecture Notes in Computer Science(), vol 12183. Springer, Cham. https://doi.org/10.1007/978-3-030-49065-2_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-49065-2_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-49064-5

  • Online ISBN: 978-3-030-49065-2

  • eBook Packages: Computer ScienceComputer Science (R0)